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DBMS → Transactions 1

ROLLBACK
Undoes changes since last COMMIT or SAVEPOINT
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DBMS → Introduction to DBMS 24

SAVEPOINT creates
Named marker within transaction for partial rollback
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UNIQUE constraint prevents
Duplicate non-NULL values in a column
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CHECK constraint ensures
Column values satisfy a boolean expression
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ON DELETE CASCADE
Automatically deletes child rows when parent row deleted
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COALESCE(NULL,NULL,5,10) returns
5
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NULLIF(5,5) returns
NULL
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% in SQL LIKE matches
Zero or more characters
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BETWEEN a AND b is
Inclusive on both ends (a ≤ value ≤ b)
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WHERE col IN (1,2,3) equals
col=1 OR col=2 OR col=3
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CASE expression provides
Conditional IF-THEN-ELSE logic within SQL query
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X→Y (X functionally determines Y) means
For each X value there is exactly one corresponding Y value
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Armstrong's Reflexivity: if Y⊆X then
X→Y
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Armstrong's Augmentation: if X→Y then
XZ→YZ
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Armstrong's Transitivity: if X→Y and Y→Z then
X→Z
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Armstrong's axioms are
Sound and complete
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Attribute closure X+ is computed by
Starting with X and iteratively adding attributes determined by FD set F
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If A+ = all attributes of R(A,B,C,D) then A is
A superkey determining all attributes
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A canonical cover (Fc) is
Minimal equivalent FD set with no redundancy
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A prime attribute is
Part of at least one candidate key
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A non-prime attribute is
NOT part of any candidate key
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Dependency preservation means
Every FD can be verified from decomposed relations without joins
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Union rule from Armstrong: if X→Y and X→Z then
X→YZ
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Decomposition rule: if X→YZ then
X→Y and X→Z
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Trivial FD X→Y means
Y⊆X (B is a subset of A)
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DBMS → Normalization 13

Normalization is which database design approach?
Bottom-up
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1NF requires
All attributes atomic and no repeating groups
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Which violates 1NF?
Column storing comma-separated multiple phone numbers
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2NF is violated by
Partial dependencies: non-key attribute depends on part of composite PK
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3NF is violated when
Non-key attribute transitively depends on PK through another non-key attribute
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BCNF requires: for every non-trivial FD X→Y
X must be a superkey
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3NF decomposition guarantees
Both lossless join AND dependency preservation
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BCNF decomposition guarantees
Lossless join always but may NOT preserve all dependencies
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4NF eliminates
Multi-valued dependencies (MVDs)
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5NF eliminates
Join dependencies
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Insertion anomaly means
Cannot insert certain data without inserting unrelated data
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Deletion anomaly means
Deleting one row unintentionally destroys other needed information
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Update anomaly means
Updating one fact requires changing multiple rows causing inconsistency risk
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DBMS → Joins 2

Lossless-join decomposition means
Join of decomposed relations gives exactly the original relation without spurious tuples
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Lossless-join condition for R→R1,R2: the condition is
R1∩R2 → R1 OR R1∩R2 → R2 (intersection is superkey in one decomposed relation)
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